{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Dropbox\Alecia\Stability of Political Attitudes\Replication Prep\GSS\data\comparisons.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}10 Dec 2025, 19:20:48
{txt}
{com}. 
. use "GSS_2006_2020RecodedAppendedPanels.dta"
{txt}
{com}. 
. generate wavefe = yearintv
{txt}
{com}. 
. xtset panel_id yearintv, delta(2)
{res}
{col 1}{txt:Panel variable: }{res:panel_id}{txt: (unbalanced)}
{p 1 16 2}{txt:Time variable: }{res:yearintv}{txt:, }{res:{bind:2006}}{txt: to }{res:{bind:2020}}{txt:, but with gaps}{p_end}
{txt}{col 10}Delta: {res}2 units
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. /**Interclass correlation coefficients*/
. 
.         /*Ideological Identification*/
. 
. icc polviews panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}766{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1205
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}              polviews{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5989584{col 37}{text}  {col 39}{result}{space 3} .5698018{col 51}{space 3} .6272814
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .8175356{col 37}{text}  {col 39}{result}{space 3} .7989356{col 51}{space 3} .8346825
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1204.0{txt}, {res}2408.0{txt}) = {res}5.49{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc polviews panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}791{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1196
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}              polviews{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .6173874{col 37}{text}  {col 39}{result}{space 3}  .588966{col 51}{space 3} .6449274
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .8287915{col 37}{text}  {col 39}{result}{space 3} .8112733{col 51}{space 3} .8449366
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1195.0{txt}, {res}2390.0{txt}) = {res}5.85{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc polviews panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}784{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1228
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}              polviews{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .6526789{col 37}{text}  {col 39}{result}{space 3} .6263573{col 51}{space 3} .6780788
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .8493418{col 37}{text}  {col 39}{result}{space 3} .8341367{col 51}{space 3} .8633703
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1227.0{txt}, {res}2454.0{txt}) = {res}6.64{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> icc polviews panel_id yearintv if panel== 4,mixed absolute
> */
. 
. 
. 
. 
.         /*Government spending too much, too little, or about the right amount on military, armaments and defense.*/
. 
. icc rec_natarms panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}382{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     605
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natarms{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .4790221{col 37}{text}  {col 39}{result}{space 3} .4314579{col 51}{space 3} .5256586
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7339294{col 37}{text}  {col 39}{result}{space 3} .6948107{col 51}{space 3} .7687625
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}604.0{txt}, {res}1208.0{txt}) = {res}3.79{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natarms panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}418{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     574
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natarms{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5108626{col 37}{text}  {col 39}{result}{space 3} .4629005{col 51}{space 3} .5574915
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7580594{col 37}{text}  {col 39}{result}{space 3} .7211033{col 51}{space 3} .7907745
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}573.0{txt}, {res}1146.0{txt}) = {res}4.19{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natarms panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}390{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     613
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natarms{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2}  .517361{col 37}{text}  {col 39}{result}{space 3} .4717177{col 51}{space 3} .5618077
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7627985{col 37}{text}  {col 39}{result}{space 3} .7281709{col 51}{space 3} .7936574
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}612.0{txt}, {res}1224.0{txt}) = {res}4.25{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> 
> icc rec_natarms panel_id yearintv if panel== 4,mixed absolute
> */
. 
. 
. 
.         /*Government spending too much, too little, or about the right amount on welfare.*/
. icc rec_natfare panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}396{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     592
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natfare{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5140938{col 37}{text}  {col 39}{result}{space 3} .4676797{col 51}{space 3} .5593349
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7604234{col 37}{text}  {col 39}{result}{space 3} .7249502{col 51}{space 3} .7920086
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}591.0{txt}, {res}1182.0{txt}) = {res}4.19{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natfare panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}439{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     552
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natfare{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5345422{col 37}{text}  {col 39}{result}{space 3} .4874031{col 51}{space 3} .5802571
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7750417{col 37}{text}  {col 39}{result}{space 3} .7404318{col 51}{space 3} .8057208
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}551.0{txt}, {res}1102.0{txt}) = {res}4.47{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natfare panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}397{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     604
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_natfare{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .4875922{col 37}{text}  {col 39}{result}{space 3}  .440483{col 51}{space 3} .5337392
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7405773{col 37}{text}  {col 39}{result}{space 3} .7025374{col 51}{space 3} .7744785
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}603.0{txt}, {res}1206.0{txt}) = {res}3.88{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> 
> icc rec_natfare panel_id yearintv if panel== 4,mixed absolute
> */
. 
. 
. 
.         /*Government spending too much, too little, or about the right amount on improving and protecting the environment.*/
. icc rec_natenvir panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}384{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     604
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}          rec_natenvir{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .4777689{col 37}{text}  {col 39}{result}{space 3} .4250829{col 51}{space 3} .5284759
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7329476{col 37}{text}  {col 39}{result}{space 3} .6892618{col 51}{space 3} .7707656
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}603.0{txt}, {res}1206.0{txt}) = {res}3.88{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natenvir panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}395{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     596
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}          rec_natenvir{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .4376115{col 37}{text}  {col 39}{result}{space 3} .3873172{col 51}{space 3} .4871257
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7000951{col 37}{text}  {col 39}{result}{space 3} .6547555{col 51}{space 3} .7402184
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}595.0{txt}, {res}1190.0{txt}) = {res}3.39{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_natenvir panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}383{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     616
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}          rec_natenvir{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5492393{col 37}{text}  {col 39}{result}{space 3} .5054425{col 51}{space 3} .5916806
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7851964{col 37}{text}  {col 39}{result}{space 3} .7540598{col 51}{space 3} .8129858
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}615.0{txt}, {res}1230.0{txt}) = {res}4.66{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> 
> icc rec_rec_natenvir panel_id yearintv if panel== 4,mixed absolute
> */
. 
. 
. 
. 
.         /*The number of immigrants to America nowadays should be reduced a lot, reduced a little, remain the same as it is, increased a little, or increased a lot*/
. icc rec_letin1a panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}200{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     794
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       2

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_letin1a{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5749665{col 37}{text}  {col 39}{result}{space 3} .5264611{col 51}{space 3} .6197393
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7301317{col 37}{text}  {col 39}{result}{space 3} .6897799{col 51}{space 3} .7652334
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}793.0{txt}, {res}793.0{txt}) = {res}3.70{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_letin1a panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}500{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     811
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_letin1a{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .4907021{col 37}{text}  {col 39}{result}{space 3} .4502286{col 51}{space 3} .5304448
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7429611{col 37}{text}  {col 39}{result}{space 3} .7107162{col 51}{space 3}  .772159
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}810.0{txt}, {res}1620.0{txt}) = {res}3.91{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_letin1a panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}557{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}     860
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_letin1a{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .5033326{col 37}{text}  {col 39}{result}{space 3} .4645172{col 51}{space 3} .5413987
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .7524912{col 37}{text}  {col 39}{result}{space 3} .7224089{col 51}{space 3} .7798147
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}859.0{txt}, {res}1718.0{txt}) = {res}4.04{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> 
> icc rec_letin1a panel_id yearintv if panel== 4,mixed absolute
> */
. 
. 
. 
.         /* Party Identification*/
. icc rec_partyid panel_id yearintv if panel== 1,mixed absolute
{txt}{p 0 0 2}({res}736{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1260
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_partyid{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .8149932{col 37}{text}  {col 39}{result}{space 3} .7988858{col 51}{space 3} .8302003
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .9296549{col 37}{text}  {col 39}{result}{space 3}  .922582{col 51}{space 3} .9361752
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1259.0{txt}, {res}2518.0{txt}) = {res}14.31{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_partyid panel_id yearintv if panel== 2,mixed absolute
{txt}{p 0 0 2}({res}742{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1277
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_partyid{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .8365014{col 37}{text}  {col 39}{result}{space 3} .8222419{col 51}{space 3} .8499529
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .9388334{col 37}{text}  {col 39}{result}{space 3} .9327815{col 51}{space 3} .9444251
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1276.0{txt}, {res}2552.0{txt}) = {res}16.38{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. icc rec_partyid panel_id yearintv if panel== 3,mixed absolute
{txt}{p 0 0 2}({res}749{txt} targets{txt}  omitted from computation because{txt} not rated by all raters){p_end}

Intraclass correlations
Two-way mixed-effects model
Absolute agreement

Random effects: {res}panel_id{txt}{col 34}Number of targets =  {res}    1286
{txt} Fixed effects: {res}yearintv{txt}{col 34}Number of raters  =  {res}       3

{col 1}{text}{hline 23}{c TT}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}           rec_partyid{col 24}{c |}        ICC{col 37}  {col 39}    [95% conf. interval]
{res}{col 1}{text}{hline 23}{c +}{hline 12}{hline 2}{hline 12}{hline 12}
{col 1}{text}            Individual{col 24}{c |}{result}{space 2} .8164503{col 37}{text}  {col 39}{result}{space 3} .8007671{col 51}{space 3} .8312866
{col 1}{text}               Average{col 24}{c |}{result}{space 2} .9302861{col 37}{text}  {col 39}{result}{space 3} .9234172{col 51}{space 3} .9366352
{col 1}{text}{hline 23}{c BT}{hline 12}{hline 2}{hline 12}{hline 12}
F test that
  {txt}ICC={res}0.00{txt}: F({res}1285.0{txt}, {res}2570.0{txt}) = {res}14.34{col 47}{txt}Prob > F = {res}0.000
{txt}
{com}. 
. /* cannot compute because no case (individual) observed in all waves of panel 4
> 
> icc rec_partyid panel_id yearintv if panel== 4,mixed absolute
> 
> */
. 
. 
. 
. 
. 
. 
. /**AR1 approach**/
. 
.         /*Party Identification*/
. eststo:  xtregar rec_partyid age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}    18,754
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}    10,406

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0000{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.1153{col 63}{txt}avg{col 67}={col 69}{res}       1.8
{txt}     Overall = {res}0.1122{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}20{txt}){col 67}={col 70}{res}  1156.51
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.5228   0.5228     0.6876     0.6876   0.6876

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    rec_partyid{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2}-.0000179{col 29}{space 2} .0009988{col 40}{space 1}   -0.02{col 49}{space 3}0.986{col 57}{space 4}-.0019755{col 70}{space 3} .0019396
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2}-.0100533{col 29}{space 2} .0535401{col 40}{space 1}   -0.19{col 49}{space 3}0.851{col 57}{space 4}-.1149899{col 70}{space 3} .0948834
{txt}{space 3}high school  {c |}{col 17}{res}{space 2} .0377166{col 29}{space 2} .0387462{col 40}{space 1}    0.97{col 49}{space 3}0.330{col 57}{space 4}-.0382246{col 70}{space 3} .1136578
{txt}junior college  {c |}{col 17}{res}{space 2} .0378265{col 29}{space 2} .0519373{col 40}{space 1}    0.73{col 49}{space 3}0.466{col 57}{space 4}-.0639688{col 70}{space 3} .1396218
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2}-.3228235{col 29}{space 2} .0512114{col 40}{space 1}   -6.30{col 49}{space 3}0.000{col 57}{space 4}-.4231959{col 70}{space 3}-.2224511
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2}-1.419295{col 29}{space 2} .0462612{col 40}{space 1}  -30.68{col 49}{space 3}0.000{col 57}{space 4}-1.509966{col 70}{space 3}-1.328625
{txt}{space 9}other  {c |}{col 17}{res}{space 2}-.4184889{col 29}{space 2} .0452934{col 40}{space 1}   -9.24{col 49}{space 3}0.000{col 57}{space 4}-.5072623{col 70}{space 3}-.3297156
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2} -.226572{col 29}{space 2} .0339851{col 40}{space 1}   -6.67{col 49}{space 3}0.000{col 57}{space 4}-.2931816{col 70}{space 3}-.1599625
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2}  .000212{col 29}{space 2} .0377862{col 40}{space 1}    0.01{col 49}{space 3}0.996{col 57}{space 4}-.0738476{col 70}{space 3} .0742715
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2} .1242609{col 29}{space 2} .0336536{col 40}{space 1}    3.69{col 49}{space 3}0.000{col 57}{space 4} .0583011{col 70}{space 3} .1902208
{txt}{space 11}888  {c |}{col 17}{res}{space 2} .1350407{col 29}{space 2} .0444632{col 40}{space 1}    3.04{col 49}{space 3}0.002{col 57}{space 4} .0478945{col 70}{space 3} .2221869
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.0420853{col 29}{space 2} .0566853{col 40}{space 1}   -0.74{col 49}{space 3}0.458{col 57}{space 4}-.1531865{col 70}{space 3} .0690159
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.0393082{col 29}{space 2} .0583764{col 40}{space 1}   -0.67{col 49}{space 3}0.501{col 57}{space 4}-.1537239{col 70}{space 3} .0751074
{txt}{space 13}4  {c |}{col 17}{res}{space 2}-.0641588{col 29}{space 2} .0587307{col 40}{space 1}   -1.09{col 49}{space 3}0.275{col 57}{space 4}-.1792688{col 70}{space 3} .0509512
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2008  {c |}{col 17}{res}{space 2}-.1535497{col 29}{space 2} .0287862{col 40}{space 1}   -5.33{col 49}{space 3}0.000{col 57}{space 4}-.2099696{col 70}{space 3}-.0971298
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} -.105137{col 29}{space 2} .0305441{col 40}{space 1}   -3.44{col 49}{space 3}0.001{col 57}{space 4}-.1650024{col 70}{space 3}-.0452717
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.0979403{col 29}{space 2} .0360334{col 40}{space 1}   -2.72{col 49}{space 3}0.007{col 57}{space 4}-.1685646{col 70}{space 3}-.0273161
{txt}{space 10}2014  {c |}{col 17}{res}{space 2}-.0946584{col 29}{space 2} .0437135{col 40}{space 1}   -2.17{col 49}{space 3}0.030{col 57}{space 4}-.1803353{col 70}{space 3}-.0089815
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} -.070452{col 29}{space 2} .0558675{col 40}{space 1}   -1.26{col 49}{space 3}0.207{col 57}{space 4}-.1799503{col 70}{space 3} .0390463
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}  3.10659{col 29}{space 2} .0791988{col 40}{space 1}   39.23{col 49}{space 3}0.000{col 57}{space 4} 2.951363{col 70}{space 3} 3.261817
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .07343041{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} 1.6211957
        {txt}sigma_e {c |} {res} .87807201
        {txt}rho_fov {c |} {res} .77318458{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est1{txt} stored)

{com}. estimates store rec_partyidar1
{txt}
{com}. 
. 
.         /*Ideological Identification*/
. eststo:  xtregar polviews age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}    18,278
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}    10,222

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0010{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.0390{col 63}{txt}avg{col 67}={col 69}{res}       1.8
{txt}     Overall = {res}0.0345{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}20{txt}){col 67}={col 70}{res}   403.80
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.3582   0.3582     0.5563     0.5563   0.5563

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       polviews{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2} .0084096{col 29}{space 2} .0007671{col 40}{space 1}   10.96{col 49}{space 3}0.000{col 57}{space 4}  .006906{col 70}{space 3} .0099131
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2} .1538976{col 29}{space 2} .0454969{col 40}{space 1}    3.38{col 49}{space 3}0.001{col 57}{space 4} .0647253{col 70}{space 3} .2430698
{txt}{space 3}high school  {c |}{col 17}{res}{space 2} .1784685{col 29}{space 2} .0323787{col 40}{space 1}    5.51{col 49}{space 3}0.000{col 57}{space 4} .1150074{col 70}{space 3} .2419296
{txt}junior college  {c |}{col 17}{res}{space 2} .1858271{col 29}{space 2} .0458476{col 40}{space 1}    4.05{col 49}{space 3}0.000{col 57}{space 4} .0959674{col 70}{space 3} .2756869
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2}-.3229501{col 29}{space 2} .0442441{col 40}{space 1}   -7.30{col 49}{space 3}0.000{col 57}{space 4}-.4096669{col 70}{space 3}-.2362333
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2} -.275123{col 29}{space 2} .0365822{col 40}{space 1}   -7.52{col 49}{space 3}0.000{col 57}{space 4}-.3468227{col 70}{space 3}-.2034232
{txt}{space 9}other  {c |}{col 17}{res}{space 2}-.1400487{col 29}{space 2} .0401855{col 40}{space 1}   -3.49{col 49}{space 3}0.000{col 57}{space 4}-.2188108{col 70}{space 3}-.0612866
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2}-.0893465{col 29}{space 2} .0262462{col 40}{space 1}   -3.40{col 49}{space 3}0.001{col 57}{space 4}-.1407881{col 70}{space 3}-.0379049
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2} .1297928{col 29}{space 2} .0370192{col 40}{space 1}    3.51{col 49}{space 3}0.000{col 57}{space 4} .0572366{col 70}{space 3} .2023491
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2} .1888016{col 29}{space 2} .0315056{col 40}{space 1}    5.99{col 49}{space 3}0.000{col 57}{space 4} .1270518{col 70}{space 3} .2505514
{txt}{space 11}888  {c |}{col 17}{res}{space 2} .2103337{col 29}{space 2} .0445815{col 40}{space 1}    4.72{col 49}{space 3}0.000{col 57}{space 4} .1229556{col 70}{space 3} .2977118
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .0572592{col 29}{space 2} .0431848{col 40}{space 1}    1.33{col 49}{space 3}0.185{col 57}{space 4}-.0273815{col 70}{space 3} .1418999
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .0157217{col 29}{space 2} .0456336{col 40}{space 1}    0.34{col 49}{space 3}0.730{col 57}{space 4}-.0737184{col 70}{space 3} .1051619
{txt}{space 13}4  {c |}{col 17}{res}{space 2}-.0802264{col 29}{space 2} .0463539{col 40}{space 1}   -1.73{col 49}{space 3}0.083{col 57}{space 4}-.1710784{col 70}{space 3} .0106256
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2008  {c |}{col 17}{res}{space 2}-.0769016{col 29}{space 2} .0305827{col 40}{space 1}   -2.51{col 49}{space 3}0.012{col 57}{space 4}-.1368426{col 70}{space 3}-.0169607
{txt}{space 10}2010  {c |}{col 17}{res}{space 2}-.0470699{col 29}{space 2} .0320164{col 40}{space 1}   -1.47{col 49}{space 3}0.142{col 57}{space 4}-.1098209{col 70}{space 3} .0156811
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.0339988{col 29}{space 2} .0378057{col 40}{space 1}   -0.90{col 49}{space 3}0.368{col 57}{space 4}-.1080967{col 70}{space 3}  .040099
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} -.096107{col 29}{space 2}  .045663{col 40}{space 1}   -2.10{col 49}{space 3}0.035{col 57}{space 4}-.1856047{col 70}{space 3}-.0066092
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .0098932{col 29}{space 2} .0440016{col 40}{space 1}    0.22{col 49}{space 3}0.822{col 57}{space 4}-.0763484{col 70}{space 3} .0961348
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 3.573294{col 29}{space 2} .0645982{col 40}{space 1}   55.32{col 49}{space 3}0.000{col 57}{space 4} 3.446684{col 70}{space 3} 3.699904
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .03704198{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} 1.0935738
        {txt}sigma_e {c |} {res} .91465165
        {txt}rho_fov {c |} {res} .58839301{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est2{txt} stored)

{com}. estimates store polviewsar1
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on military, armaments and defense.*/
. eststo:  xtregar rec_natarms age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}     9,117
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,127

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0091{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.0960{col 63}{txt}avg{col 67}={col 69}{res}       1.8
{txt}     Overall = {res}0.0800{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}20{txt}){col 67}={col 70}{res}   584.42
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.2554   0.2554     0.4476     0.4476   0.4476

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    rec_natarms{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2} .0070221{col 29}{space 2} .0005619{col 40}{space 1}   12.50{col 49}{space 3}0.000{col 57}{space 4} .0059207{col 70}{space 3} .0081235
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2} .1999715{col 29}{space 2} .0345796{col 40}{space 1}    5.78{col 49}{space 3}0.000{col 57}{space 4} .1321967{col 70}{space 3} .2677464
{txt}{space 3}high school  {c |}{col 17}{res}{space 2} .2310746{col 29}{space 2} .0245944{col 40}{space 1}    9.40{col 49}{space 3}0.000{col 57}{space 4} .1828705{col 70}{space 3} .2792787
{txt}junior college  {c |}{col 17}{res}{space 2} .2484976{col 29}{space 2} .0356854{col 40}{space 1}    6.96{col 49}{space 3}0.000{col 57}{space 4} .1785554{col 70}{space 3} .3184398
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2}-.1173789{col 29}{space 2} .0333812{col 40}{space 1}   -3.52{col 49}{space 3}0.000{col 57}{space 4}-.1828048{col 70}{space 3}-.0519529
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2}-.1253832{col 29}{space 2}  .027118{col 40}{space 1}   -4.62{col 49}{space 3}0.000{col 57}{space 4}-.1785335{col 70}{space 3} -.072233
{txt}{space 9}other  {c |}{col 17}{res}{space 2}-.1674497{col 29}{space 2} .0304788{col 40}{space 1}   -5.49{col 49}{space 3}0.000{col 57}{space 4}-.2271872{col 70}{space 3}-.1077123
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2} .1095409{col 29}{space 2} .0193692{col 40}{space 1}    5.66{col 49}{space 3}0.000{col 57}{space 4} .0715779{col 70}{space 3} .1475039
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2}-.0005436{col 29}{space 2} .0299037{col 40}{space 1}   -0.02{col 49}{space 3}0.985{col 57}{space 4}-.0591538{col 70}{space 3} .0580666
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2} .0757208{col 29}{space 2} .0246262{col 40}{space 1}    3.07{col 49}{space 3}0.002{col 57}{space 4} .0274543{col 70}{space 3} .1239874
{txt}{space 11}888  {c |}{col 17}{res}{space 2} .0604918{col 29}{space 2} .0359096{col 40}{space 1}    1.68{col 49}{space 3}0.092{col 57}{space 4}-.0098897{col 70}{space 3} .1308733
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.0001042{col 29}{space 2} .0317148{col 40}{space 1}   -0.00{col 49}{space 3}0.997{col 57}{space 4} -.062264{col 70}{space 3} .0620556
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .0428547{col 29}{space 2} .0342759{col 40}{space 1}    1.25{col 49}{space 3}0.211{col 57}{space 4}-.0243248{col 70}{space 3} .1100343
{txt}{space 13}4  {c |}{col 17}{res}{space 2}  .183605{col 29}{space 2} .0349207{col 40}{space 1}    5.26{col 49}{space 3}0.000{col 57}{space 4} .1151616{col 70}{space 3} .2520484
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2008  {c |}{col 17}{res}{space 2}-.0671777{col 29}{space 2} .0262229{col 40}{space 1}   -2.56{col 49}{space 3}0.010{col 57}{space 4}-.1185737{col 70}{space 3}-.0157818
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .0345857{col 29}{space 2} .0275283{col 40}{space 1}    1.26{col 49}{space 3}0.209{col 57}{space 4}-.0193687{col 70}{space 3} .0885402
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0257249{col 29}{space 2} .0326037{col 40}{space 1}    0.79{col 49}{space 3}0.430{col 57}{space 4}-.0381771{col 70}{space 3}  .089627
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .1201542{col 29}{space 2} .0394098{col 40}{space 1}    3.05{col 49}{space 3}0.002{col 57}{space 4} .0429125{col 70}{space 3}  .197396
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .0640926{col 29}{space 2} .0330558{col 40}{space 1}    1.94{col 49}{space 3}0.053{col 57}{space 4}-.0006956{col 70}{space 3} .1288808
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}   1.2988{col 29}{space 2} .0486678{col 40}{space 1}   26.69{col 49}{space 3}0.000{col 57}{space 4} 1.203413{col 70}{space 3} 1.394187
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .04350047{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} .50737986
        {txt}sigma_e {c |} {res} .56535801
        {txt}rho_fov {c |} {res} .44611052{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est3{txt} stored)

{com}. estimates store rec_natarmsar1
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on welfare.*/
. eststo:  xtregar rec_natfare age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}     9,056
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,107

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0051{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.0679{col 63}{txt}avg{col 67}={col 69}{res}       1.8
{txt}     Overall = {res}0.0610{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}20{txt}){col 67}={col 70}{res}   378.47
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.2634   0.2634     0.4544     0.4544   0.4544

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    rec_natfare{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2}-.0001668{col 29}{space 2} .0005642{col 40}{space 1}   -0.30{col 49}{space 3}0.768{col 57}{space 4}-.0012726{col 70}{space 3} .0009391
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2}-.0125921{col 29}{space 2} .0345198{col 40}{space 1}   -0.36{col 49}{space 3}0.715{col 57}{space 4}-.0802497{col 70}{space 3} .0550654
{txt}{space 3}high school  {c |}{col 17}{res}{space 2}-.0940552{col 29}{space 2} .0245912{col 40}{space 1}   -3.82{col 49}{space 3}0.000{col 57}{space 4}-.1422531{col 70}{space 3}-.0458572
{txt}junior college  {c |}{col 17}{res}{space 2}-.1064523{col 29}{space 2} .0354865{col 40}{space 1}   -3.00{col 49}{space 3}0.003{col 57}{space 4}-.1760047{col 70}{space 3}   -.0369
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2} .0789776{col 29}{space 2}  .033336{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0136403{col 70}{space 3}  .144315
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2} .2774966{col 29}{space 2} .0271054{col 40}{space 1}   10.24{col 49}{space 3}0.000{col 57}{space 4} .2243711{col 70}{space 3} .3306222
{txt}{space 9}other  {c |}{col 17}{res}{space 2} .1305608{col 29}{space 2} .0303731{col 40}{space 1}    4.30{col 49}{space 3}0.000{col 57}{space 4} .0710306{col 70}{space 3} .1900911
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2} .0130802{col 29}{space 2} .0194232{col 40}{space 1}    0.67{col 49}{space 3}0.501{col 57}{space 4}-.0249885{col 70}{space 3} .0511489
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2}-.1088068{col 29}{space 2} .0296207{col 40}{space 1}   -3.67{col 49}{space 3}0.000{col 57}{space 4}-.1668623{col 70}{space 3}-.0507514
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2} -.271761{col 29}{space 2} .0245281{col 40}{space 1}  -11.08{col 49}{space 3}0.000{col 57}{space 4}-.3198353{col 70}{space 3}-.2236868
{txt}{space 11}888  {c |}{col 17}{res}{space 2} -.164673{col 29}{space 2} .0355292{col 40}{space 1}   -4.63{col 49}{space 3}0.000{col 57}{space 4} -.234309{col 70}{space 3}-.0950369
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2} .0008206{col 29}{space 2}  .031743{col 40}{space 1}    0.03{col 49}{space 3}0.979{col 57}{space 4}-.0613946{col 70}{space 3} .0630357
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.0060726{col 29}{space 2} .0342269{col 40}{space 1}   -0.18{col 49}{space 3}0.859{col 57}{space 4} -.073156{col 70}{space 3} .0610108
{txt}{space 13}4  {c |}{col 17}{res}{space 2} -.032043{col 29}{space 2} .0348611{col 40}{space 1}   -0.92{col 49}{space 3}0.358{col 57}{space 4}-.1003694{col 70}{space 3} .0362834
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2008  {c |}{col 17}{res}{space 2}-.0078991{col 29}{space 2} .0259093{col 40}{space 1}   -0.30{col 49}{space 3}0.760{col 57}{space 4}-.0586803{col 70}{space 3} .0428821
{txt}{space 10}2010  {c |}{col 17}{res}{space 2}-.0858682{col 29}{space 2} .0271954{col 40}{space 1}   -3.16{col 49}{space 3}0.002{col 57}{space 4}-.1391701{col 70}{space 3}-.0325663
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.1351554{col 29}{space 2} .0322394{col 40}{space 1}   -4.19{col 49}{space 3}0.000{col 57}{space 4}-.1983434{col 70}{space 3}-.0719674
{txt}{space 10}2014  {c |}{col 17}{res}{space 2}-.1514859{col 29}{space 2} .0389421{col 40}{space 1}   -3.89{col 49}{space 3}0.000{col 57}{space 4}-.2278109{col 70}{space 3}-.0751608
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0778014{col 29}{space 2} .0330643{col 40}{space 1}   -2.35{col 49}{space 3}0.019{col 57}{space 4}-.1426061{col 70}{space 3}-.0129966
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 2.099243{col 29}{space 2} .0486747{col 40}{space 1}   43.13{col 49}{space 3}0.000{col 57}{space 4} 2.003842{col 70}{space 3} 2.194643
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .05343744{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} .51111166
        {txt}sigma_e {c |} {res} .55578472
        {txt}rho_fov {c |} {res}  .4582013{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est4{txt} stored)

{com}. estimates store rec_natfarear1
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on improving and protecting the environment.*/
. eststo:  xtregar rec_natenvir age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}     9,146
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,133

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0241{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.0489{col 63}{txt}avg{col 67}={col 69}{res}       1.8
{txt}     Overall = {res}0.0430{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}20{txt}){col 67}={col 70}{res}   360.63
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.2626   0.2626     0.4524     0.4524   0.4524

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   rec_natenvir{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2}-.0052431{col 29}{space 2} .0004701{col 40}{space 1}  -11.15{col 49}{space 3}0.000{col 57}{space 4}-.0061645{col 70}{space 3}-.0043218
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2}-.0857138{col 29}{space 2} .0287915{col 40}{space 1}   -2.98{col 49}{space 3}0.003{col 57}{space 4}-.1421441{col 70}{space 3}-.0292836
{txt}{space 3}high school  {c |}{col 17}{res}{space 2}-.0362669{col 29}{space 2} .0204314{col 40}{space 1}   -1.78{col 49}{space 3}0.076{col 57}{space 4}-.0763117{col 70}{space 3} .0037778
{txt}junior college  {c |}{col 17}{res}{space 2}-.0259508{col 29}{space 2} .0295265{col 40}{space 1}   -0.88{col 49}{space 3}0.379{col 57}{space 4}-.0838216{col 70}{space 3}   .03192
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2} .0566119{col 29}{space 2} .0277889{col 40}{space 1}    2.04{col 49}{space 3}0.042{col 57}{space 4} .0021467{col 70}{space 3} .1110772
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2} .0669144{col 29}{space 2} .0225321{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} .0227523{col 70}{space 3} .1110766
{txt}{space 9}other  {c |}{col 17}{res}{space 2}-.0482015{col 29}{space 2}  .025221{col 40}{space 1}   -1.91{col 49}{space 3}0.056{col 57}{space 4}-.0976339{col 70}{space 3} .0012308
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2} .0994786{col 29}{space 2} .0161764{col 40}{space 1}    6.15{col 49}{space 3}0.000{col 57}{space 4} .0677734{col 70}{space 3} .1311838
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2}-.0205728{col 29}{space 2} .0246516{col 40}{space 1}   -0.83{col 49}{space 3}0.404{col 57}{space 4}-.0688891{col 70}{space 3} .0277434
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2} -.006668{col 29}{space 2} .0203797{col 40}{space 1}   -0.33{col 49}{space 3}0.744{col 57}{space 4}-.0466114{col 70}{space 3} .0332755
{txt}{space 11}888  {c |}{col 17}{res}{space 2}-.0675294{col 29}{space 2} .0297164{col 40}{space 1}   -2.27{col 49}{space 3}0.023{col 57}{space 4}-.1257724{col 70}{space 3}-.0092864
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.0078254{col 29}{space 2} .0264592{col 40}{space 1}   -0.30{col 49}{space 3}0.767{col 57}{space 4}-.0596844{col 70}{space 3} .0440336
{txt}{space 13}3  {c |}{col 17}{res}{space 2}-.0218768{col 29}{space 2} .0285798{col 40}{space 1}   -0.77{col 49}{space 3}0.444{col 57}{space 4}-.0778922{col 70}{space 3} .0341385
{txt}{space 13}4  {c |}{col 17}{res}{space 2}-.0263904{col 29}{space 2} .0290002{col 40}{space 1}   -0.91{col 49}{space 3}0.363{col 57}{space 4}-.0832297{col 70}{space 3} .0304489
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2008  {c |}{col 17}{res}{space 2}-.0288634{col 29}{space 2} .0215913{col 40}{space 1}   -1.34{col 49}{space 3}0.181{col 57}{space 4}-.0711816{col 70}{space 3} .0134547
{txt}{space 10}2010  {c |}{col 17}{res}{space 2}-.1567149{col 29}{space 2} .0226615{col 40}{space 1}   -6.92{col 49}{space 3}0.000{col 57}{space 4}-.2011307{col 70}{space 3}-.1122991
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.1476643{col 29}{space 2}  .026809{col 40}{space 1}   -5.51{col 49}{space 3}0.000{col 57}{space 4}-.2002089{col 70}{space 3}-.0951197
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} -.108028{col 29}{space 2} .0324416{col 40}{space 1}   -3.33{col 49}{space 3}0.001{col 57}{space 4}-.1716124{col 70}{space 3}-.0444436
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0828766{col 29}{space 2} .0274168{col 40}{space 1}   -3.02{col 49}{space 3}0.003{col 57}{space 4}-.1366125{col 70}{space 3}-.0291407
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 2.866609{col 29}{space 2} .0405261{col 40}{space 1}   70.73{col 49}{space 3}0.000{col 57}{space 4} 2.787179{col 70}{space 3} 2.946039
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .05723183{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} .42853135
        {txt}sigma_e {c |} {res} .46712008
        {txt}rho_fov {c |} {res} .45699529{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est5{txt} stored)

{com}. estimates store rec_natenvirar1
{txt}
{com}. 
.         /*The number of immigrants to America nowadays should be reduced a lot, reduced a little, remain the same as it is, increased a little, or increased a lot*/
. eststo:  xtregar rec_letin1a  age ib3.degree ib1.race ib1.sex ib1.rec_income ib1.panel i.wavefe, re  
{txt}note: {bf:2018.wavefe} omitted because of collinearity.

RE GLS regression with AR(1) disturbances{col 49}Number of obs{col 67}={col 69}{res}    11,025
{txt}Group variable: {res}panel_id{txt}{col 49}Number of groups{col 67}={col 69}{res}     6,571

{txt}R-squared:{col 49}Obs per group:
     Within  = {res}0.0023{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     Between = {res}0.1051{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     Overall = {res}0.0899{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}Wald chi2({res}19{txt}){col 67}={col 70}{res}   782.33
{txt}corr(u_i, Xb) = {res}0{txt} (assumed){col 49}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{hline 19} theta {hline 20}
  min      5%       median        95%      max
{res}0.2697   0.2697     0.3949     0.4720   0.4720

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    rec_letin1a{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      z{col 49}   P>|z|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}age {c |}{col 17}{res}{space 2}-.0064484{col 29}{space 2} .0006939{col 40}{space 1}   -9.29{col 49}{space 3}0.000{col 57}{space 4}-.0078084{col 70}{space 3}-.0050884
{txt}{space 15} {c |}
{space 9}degree {c |}
lt high school  {c |}{col 17}{res}{space 2}-.2998564{col 29}{space 2} .0431324{col 40}{space 1}   -6.95{col 49}{space 3}0.000{col 57}{space 4}-.3843944{col 70}{space 3}-.2153185
{txt}{space 3}high school  {c |}{col 17}{res}{space 2}-.3893987{col 29}{space 2} .0307554{col 40}{space 1}  -12.66{col 49}{space 3}0.000{col 57}{space 4}-.4496782{col 70}{space 3}-.3291192
{txt}junior college  {c |}{col 17}{res}{space 2}-.3491928{col 29}{space 2} .0449794{col 40}{space 1}   -7.76{col 49}{space 3}0.000{col 57}{space 4}-.4373507{col 70}{space 3}-.2610349
{txt}{space 6}graduate  {c |}{col 17}{res}{space 2} .1593923{col 29}{space 2} .0430282{col 40}{space 1}    3.70{col 49}{space 3}0.000{col 57}{space 4} .0750586{col 70}{space 3} .2437261
{txt}{space 15} {c |}
{space 11}race {c |}
{space 9}black  {c |}{col 17}{res}{space 2} .3133047{col 29}{space 2} .0332593{col 40}{space 1}    9.42{col 49}{space 3}0.000{col 57}{space 4} .2481176{col 70}{space 3} .3784918
{txt}{space 9}other  {c |}{col 17}{res}{space 2}   .46962{col 29}{space 2} .0398882{col 40}{space 1}   11.77{col 49}{space 3}0.000{col 57}{space 4} .3914406{col 70}{space 3} .5477994
{txt}{space 15} {c |}
{space 12}sex {c |}
{space 8}female  {c |}{col 17}{res}{space 2}-.0160527{col 29}{space 2} .0238703{col 40}{space 1}   -0.67{col 49}{space 3}0.501{col 57}{space 4}-.0628377{col 70}{space 3} .0307323
{txt}{space 15} {c |}
{space 5}rec_income {c |}
{space 1}$1000 to 2999  {c |}{col 17}{res}{space 2}-.0929898{col 29}{space 2} .0380375{col 40}{space 1}   -2.44{col 49}{space 3}0.014{col 57}{space 4} -.167542{col 70}{space 3}-.0184376
{txt}{space 1}$3000 to 3999  {c |}{col 17}{res}{space 2}-.0680954{col 29}{space 2} .0314047{col 40}{space 1}   -2.17{col 49}{space 3}0.030{col 57}{space 4}-.1296476{col 70}{space 3}-.0065432
{txt}{space 11}888  {c |}{col 17}{res}{space 2}-.1226487{col 29}{space 2} .0457381{col 40}{space 1}   -2.68{col 49}{space 3}0.007{col 57}{space 4}-.2122937{col 70}{space 3}-.0330036
{txt}{space 15} {c |}
{space 10}panel {c |}
{space 13}2  {c |}{col 17}{res}{space 2}-.0054919{col 29}{space 2} .0391204{col 40}{space 1}   -0.14{col 49}{space 3}0.888{col 57}{space 4}-.0821665{col 70}{space 3} .0711826
{txt}{space 13}3  {c |}{col 17}{res}{space 2} .0090046{col 29}{space 2} .0415188{col 40}{space 1}    0.22{col 49}{space 3}0.828{col 57}{space 4}-.0723709{col 70}{space 3}   .09038
{txt}{space 13}4  {c |}{col 17}{res}{space 2} .4299805{col 29}{space 2} .0432191{col 40}{space 1}    9.95{col 49}{space 3}0.000{col 57}{space 4} .3452726{col 70}{space 3} .5146884
{txt}{space 15} {c |}
{space 9}wavefe {c |}
{space 10}2010  {c |}{col 17}{res}{space 2} .0572006{col 29}{space 2} .0241142{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0099377{col 70}{space 3} .1044635
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0985565{col 29}{space 2} .0291687{col 40}{space 1}    3.38{col 49}{space 3}0.001{col 57}{space 4}  .041387{col 70}{space 3}  .155726
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .1598349{col 29}{space 2} .0394695{col 40}{space 1}    4.05{col 49}{space 3}0.000{col 57}{space 4} .0824762{col 70}{space 3} .2371937
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.1571917{col 29}{space 2} .0395943{col 40}{space 1}   -3.97{col 49}{space 3}0.000{col 57}{space 4}-.2347951{col 70}{space 3}-.0795883
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}  2.89662{col 29}{space 2} .0616848{col 40}{space 1}   46.96{col 49}{space 3}0.000{col 57}{space 4}  2.77572{col 70}{space 3}  3.01752
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         rho_ar {c |} {res} .01086591{txt}   (estimated autocorrelation coefficient)
        sigma_u {c |} {res} .71735519
        {txt}sigma_e {c |} {res}  .7668692
        {txt}rho_fov {c |} {res} .46667689{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}
({res}est6{txt} stored)

{com}. estimates store rec_letin1aar1 
{txt}
{com}. 
. /*combine estimates from six models into one table for paper*/
. esttab rec_partyidar1 polviewsar1 rec_natarmsar1 rec_natfarear1 rec_natenvirar1 rec_letin1aar1  using gssar1.csv, replace se stat(rho_ar sigma_u sigma_e rho_fov N N_g) star(* 0.10 ** 0.05 *** 0.01) t(3) b(3)
{res}{txt}{p 0 4 2}
(file {bf}
gssar1.csv{rm}
not found)
{p_end}
(output written to {browse  `"gssar1.csv"'})

{com}. 
. 
. 
. 
. 
. 
. /*Arellano-Bond linear dynamic panel-data estimation approach*/
. 
. /*cannot compute because artests() exceed the number of time periods*/
. //Error: Equation not identified. Regessors outnumber instruments.
. 
. /* Dropping singleton observations did not fix the issue.
> //bysort panel_id (yearintv): drop if _N==1
> */
. 
. 
. /* Commented out because we could not estimate the Arellano-Bond linear dynamic panel-data estimates due to the error discribed above.
> 
>  
> char degree[omit] 3
> 
> char race[omit] 1 
> char sex[omit] 1 
> char rec_income[omit] 1  
> char panel[omit] 1
> char wavefe[omit] 2006
> 
> 
>         /*Ideological Identification*/
> eststo: xi:  xtabond polviews age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store polviewsdynamic 
> 
>         /*Party Identification*/
> eststo: xi:  xtabond rec_partyid age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store rec_partyiddynamic 
> 
>         /*Government spending too much, too little, or about the right amount on military, armaments and defense.*/
> eststo: xi:  xtabond rec_natarms age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store rec_natarmsdynamic 
> 
> 
>         /*Government spending too much, too little, or about the right amount on welfare.*/
> eststo: xi:  xtabond rec_natfare age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store rec_natfaredynamic 
> 
>         /*Government spending too much, too little, or about the right amount on improving and protecting the environment.*/
> eststo: xi:  xtabond rec_natenvir age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store rec_natenvirdynamic 
> 
>         /*The number of immigrants to America nowadays should be reduced a lot, reduced a little, remain the same as it is, increased a little, or increased a lot*/
> eststo: xi:  xtabond rec_letin1a age i.degree i.race i.sex i.rec_income i.panel i.wavefe, lags(1) artests(2)
> estimates store rec_letin1adynamic 
> 
>         /*combine estimates from six models into one table for paper*/
> esttab   polviewsdynamic rec_partyiddynamic rec_natarmsdynamic rec_natfaredynamic rec_natenvirdynamic rec_letin1adynamic using gssdynamic.csv, replace se
> 
> */
. 
. 
. 
. 
. 
. 
. /*Rolling correlation*/
. 
. /*removing explanatory variables from dataset and reshaping dataset to wide*/
. 
. keep panel_id yearintv polviews rec_natarms rec_natfare rec_natenvir rec_letin1a rec_partyid
{txt}
{com}. 
. reshape wide polviews rec_natarms rec_natfare rec_natenvir rec_letin1a rec_partyid, i(panel_id ) j(yearintv)
{txt}(j = 2006 2008 2010 2012 2014 2016 2018 2020)

Data{col 36}Long{col 43}->{col 48}Wide
{hline 77}
Number of observations     {res}      21,648   {txt}->   {res}11,282      
{txt}Number of variables        {res}           8   {txt}->   {res}49          
{txt}j variable (8 values)          {res}yearintv   {txt}->   (dropped)
xij variables:
                               {res}polviews   {txt}->   {res}polviews2006 polviews2008 ... polviews2020
                            rec_natarms   {txt}->   {res}rec_natarms2006 rec_natarms2008 ... rec_natarms2020
                            rec_natfare   {txt}->   {res}rec_natfare2006 rec_natfare2008 ... rec_natfare2020
                           rec_natenvir   {txt}->   {res}rec_natenvir2006 rec_natenvir2008 ... rec_natenvir2020
                            rec_letin1a   {txt}->   {res}rec_letin1a2006 rec_letin1a2008 ... rec_letin1a2020
                            rec_partyid   {txt}->   {res}rec_partyid2006 rec_partyid2008 ... rec_partyid2020
{txt}{hline 77}

{com}. 
. save "gss_correlations.dta", replace
{txt}{p 0 4 2}
(file {bf}
gss_correlations.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
gss_correlations.dta{rm}
saved
{p_end}

{com}. 
. 
. 
.         /*Ideological Identification*/
. asdoc pwcorr polviews*, replace save(polviews_corr.doc)
{res}
             {txt}{c |} pol~2006 pol~2008 pol~2010 pol~2012 pol~2014 pol~2016 pol~2018 pol~2020
{hline 13}{c +}{hline 72}
{res}{txt}polviews2006 {c |} {res}  1.0000 
{txt}polviews2008 {c |} {res}  0.5766   1.0000 
{txt}polviews2010 {c |} {res}  0.5699   0.6130   1.0000 
{txt}polviews2012 {c |} {res}       .   0.5952   0.6390   1.0000 
{txt}polviews2014 {c |} {res}       .        .   0.6325   0.6446   1.0000 
{txt}polviews2016 {c |} {res}       .        .        .        .        .   1.0000 
{txt}polviews2018 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}polviews2020 {c |} {res}       .        .        .        .        .   0.6030   0.6842   1.0000 
Click to Open File:  {browse "polviews_corr.doc"}
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on military, armaments and defense.*/
. asdoc pwcorr rec_natarms*, replace save(rec_natarms_corr.doc)
{res}
             {txt}{c |} re~s2006 re~s2008 re~s2010 re~s2012 re~s2014 re~s2016 re~s2018 re~s2020
{hline 13}{c +}{hline 72}
{res}{txt}rec_natar~06 {c |} {res}  1.0000 
{txt}rec_natar~08 {c |} {res}  0.4694   1.0000 
{txt}rec_natar~10 {c |} {res}  0.4412   0.5100   1.0000 
{txt}rec_natarm~2 {c |} {res}       .   0.4836   0.5558   1.0000 
{txt}rec_natarm~4 {c |} {res}       .        .   0.4951   0.5168   1.0000 
{txt}rec_natar~16 {c |} {res}       .        .        .        .        .   1.0000 
{txt}rec_natar~18 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}rec_natar~20 {c |} {res}       .        .        .        .        .   0.5537   0.5767   1.0000 
Click to Open File:  {browse "rec_natarms_corr.doc"}
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on welfare.*/
. asdoc pwcorr rec_natfare*, replace save(rec_natfare_corr.doc)
{res}
             {txt}{c |} re~e2006 re~e2008 re~e2010 re~e2012 re~e2014 re~e2016 re~e2018 re~e2020
{hline 13}{c +}{hline 72}
{res}{txt}rec_natfa~06 {c |} {res}  1.0000 
{txt}rec_natfa~08 {c |} {res}  0.5047   1.0000 
{txt}rec_natfa~10 {c |} {res}  0.4543   0.5333   1.0000 
{txt}rec_natfar~2 {c |} {res}       .   0.4755   0.5329   1.0000 
{txt}rec_natfar~4 {c |} {res}       .        .   0.4818   0.5160   1.0000 
{txt}rec_natfa~16 {c |} {res}       .        .        .        .        .   1.0000 
{txt}rec_natfa~18 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}rec_natfa~20 {c |} {res}       .        .        .        .        .   0.4617   0.5616   1.0000 
Click to Open File:  {browse "rec_natfare_corr.doc"}
{txt}
{com}. 
.         /*Government spending too much, too little, or about the right amount on improving and protecting the environment.*/
. asdoc pwcorr rec_natenvir*, replace save(rec_natenvir_corr.doc)
{res}
             {txt}{c |} re~r2006 re~r2008 re~r2010 re~r2012 re~r2014 re~r2016 re~r2018 re~r2020
{hline 13}{c +}{hline 72}
{res}{txt}rec_naten~06 {c |} {res}  1.0000 
{txt}rec_naten~08 {c |} {res}  0.4638   1.0000 
{txt}rec_naten~10 {c |} {res}  0.4596   0.4883   1.0000 
{txt}rec_natenv~2 {c |} {res}       .   0.3708   0.5461   1.0000 
{txt}rec_natenv~4 {c |} {res}       .        .   0.5142   0.5784   1.0000 
{txt}rec_naten~16 {c |} {res}       .        .        .        .        .   1.0000 
{txt}rec_naten~18 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}rec_naten~20 {c |} {res}       .        .        .        .        .   0.4938   0.5117   1.0000 
Click to Open File:  {browse "rec_natenvir_corr.doc"}
{txt}
{com}. 
.         /*The number of immigrants to America nowadays should be reduced a lot, reduced a little, remain the same as it is, increased a little, or increased a lot*/
. asdoc pwcorr rec_letin1a*, replace save(rec_letin1a_corr.doc)
{res}
             {txt}{c |} rec_l~06 rec_l~08 rec_l~10 rec_le~2 rec_le~4 rec_l~16 rec_l~18 rec_l~20
{hline 13}{c +}{hline 72}
{res}{txt}rec_let~2006 {c |} {res}       . 
{txt}rec_let~2008 {c |} {res}       .   1.0000 
{txt}rec_let~2010 {c |} {res}       .   0.5063   1.0000 
{txt}rec_let~2012 {c |} {res}       .   0.5093   0.4943   1.0000 
{txt}rec_let~2014 {c |} {res}       .        .   0.4865   0.5199   1.0000 
{txt}rec_let~2016 {c |} {res}       .        .        .        .        .   1.0000 
{txt}rec_let~2018 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}rec_let~2020 {c |} {res}       .        .        .        .        .   0.4936   0.5456   1.0000 
Click to Open File:  {browse "rec_letin1a_corr.doc"}
{txt}
{com}. 
.         /*Party Identification*/
. asdoc pwcorr rec_partyid*, replace save(rec_partyid_corr.doc)
{res}
             {txt}{c |} rec_p~06 rec_p~08 rec_p~10 rec_pa~2 rec_pa~4 rec_p~16 rec_p~18 rec_p~20
{hline 13}{c +}{hline 72}
{res}{txt}rec_par~2006 {c |} {res}  1.0000 
{txt}rec_par~2008 {c |} {res}  0.8265   1.0000 
{txt}rec_par~2010 {c |} {res}  0.7764   0.8316   1.0000 
{txt}rec_par~2012 {c |} {res}       .   0.8153   0.8412   1.0000 
{txt}rec_par~2014 {c |} {res}       .        .   0.7896   0.8283   1.0000 
{txt}rec_par~2016 {c |} {res}       .        .        .        .        .   1.0000 
{txt}rec_par~2018 {c |} {res}       .        .        .        .        .        .   1.0000 
{txt}rec_par~2020 {c |} {res}       .        .        .        .        .   0.7312   0.8129   1.0000 
Click to Open File:  {browse "rec_partyid_corr.doc"}
{txt}
{com}. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Dropbox\Alecia\Stability of Political Attitudes\Replication Prep\GSS\data\comparisons.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}10 Dec 2025, 19:20:51
{txt}{.-}
{smcl}
{txt}{sf}{ul off}